Analysis of key economic sectors promoting local economic development (LED) for strategy development in the Capricorn region, Limpopo Province

Abstract

The saga encompassing the economy of South Africa during the apartheid era finally came to an end after an expansive series of negotiations among political parties which led to the first ever free elections in the Republic in 1994. Thus, such free elections gave birth to democracy in South Africa with the introduction of local economic development (LED) to improve local economies. Despite the introduction of local economic development (LED), unemployment and poverty remain common to the majority of South Africans. This is illustrated by the fact that the majority of the people in South Africa are without jobs. As an attempt to alleviate such problems, the government has made efforts to minimise unemployment but to no avail as the unemployment rate, for example in Limpopo remained high at 38.4 percent compared to 34 percent in 1994. In addition, the poverty rate in the Capricorn District municipality is recorded at 41.1 percent which is significantly high. Thus, a combination of unemployment and poverty has harboured poor economic growth in the region. In spite of these epidemics, the key sectors are supposed to contribute to or improve local development. Therefore, the aim of the study was to analyse the contribution of key sectors to LED in the Capricorn District. To achieve the aim of the study, the study employed a quantitative research methodology to analyse key economic sectors that contribute to local economic development. The secondary annual data of four municipalities namely Blouberg, Molemole, Polokwane and Lepelle-Nkumpi which comprise the Capricorn District Municipality was used. Notable is that, this secondary annual data was from 1996 to 2015. This gave the researcher a sample size of nineteen years. The data included the local economic development index (LEDI) economic growth (lngrowth), employment (lnemploy) and poverty alleviation (lnnon-poor) as the proxies for local economic development. Thus, the local economic development index, economic growth, employment and poverty alleviation were used as dependent variables. The productivity of all the key sectors in the Capricorn District Municipality were used as independent variables such as the community service sector, trade sector, agriculture sector, tourismsector, construction sector, finance sector, mining sector, manufacturing sector, electricity sector and transport sector. The data was obtained from the Global Insight and the statistical tests were thus used to analyse the trend analysis, descriptive statistics, correlation and a unit root test. The study further employed a panel pooled mean group (PMG) model, based on the Autoregressive Distributed Lag (ARDL) to test the short-run and long-run relationship. Therefore, four models were estimated namely the local economic development index, economic growth, employment and poverty alleviation. The results of the first model (with LEDI as a dependent variable) showed a positive relationship between the productivity of community service sector, trade sector, construction sector, the finance sector, electricity sector and local economic development. In contrast, the productivity in the agriculture and manufacturing sectors had an inverse relationship with local economic development. The short run showed that 68% of disequilibrium in the municipality is reinstated in the next period provided these sectors improve to influence local economic development. Thus, it takes about 1.45 years for local economic development to adjust to change in the productivity of the key sectors. In the short-run analysis, the productivity in the community service sector, trade sector, agriculture sector and manufacturing sector contributed to local economic development in the short-run. The productivity of the finance sector, construction sector and electricity sector, however, were found to negatively affect local economic development. The second model (with economic growth as a dependent variable) revealed a positive relationship between the productivity of the construction sector, community service sector, finance sector, manufacturing sector, trade sector and transport sector and economic growth in the long-run. The mining sector and tourism sector, however, revealed a negative relationship with economic growth. The short run showed that 48% of disequilibrium in the municipality is reinstated in the next period, thus it takes 2.05 years for economic growth to adjust to change in the productivity of the key sectors. In the short run analysis, the productivity of the construction sector, finance sector, manufacturing sector, mining sector and tourism sector contributed to economic growth in the short-run. The results of the third model, with employment as a dependent variable, showed a positive relationship between the productivity of the trade sector, the tourism sector, the finance sector and employment in the long-run. On the other hand, the productivity of the construction sector, mining sector, agricultural sector, community service sector and manufacturing sector revealed an inverse relationship with employment. In the short-run, the employment model indicated a speed of adjustment of 46 percent. Thus, it takes about 2.13 years for employment to fully adjust to change in the productivity of the key sectors. The key sectors that contributed to employment in the short-run were agriculture, community service sector and manufacturing sector. In contrast, the productivity of the construction sector, finance sector, mining sector, tourism sector and trade sector influenced employment negatively. Furthermore, the results of the last model, with poverty alleviation as a dependent variable showed a positive relationship between the productivity of the tourism sector, finance sector, electricity sector, trade sector and poverty alleviation in the long-run. Conversely, a negative association between poverty and the productivity of the manufacturing, agriculture and construction sectors was established. In the short run, the poverty alleviation model showed a speed of adjustment of -0.6750. Thus, it takes 1.4 years for poverty alleviation to be reinstated with the productivity of key sectors. The key sectors that contributed to poverty alleviation in the short-run were the manufacturing and finance sector. Noteworthy is that, the manufacturing and finance sectors were the most critical sectors promoting LED in the Capricorn District Municipality since, economic growth, poverty alleviation and employment were the most important economic elements in local economic development. As a result thereof, anything that is a barrier to economic growth, poverty alleviation and employment should be eliminated. Thus, the study formulated a strategy for policy implications such as restructuring of agricultural sector, infrastructure development, ensuring capacity of all essential services, improving production methods, prioritising important projects, investing in skill development and technical skills.